Trajectory Recovery

Trajectory recovery focuses on reconstructing complete and accurate movement paths from incomplete or noisy data, addressing challenges like sparse GPS readings or obscured visual observations. Current research emphasizes developing robust algorithms, including transformer-based models and diffusion models, often incorporating spatial constraints (e.g., road networks) or auxiliary information (e.g., user profiles, camera data) to improve accuracy. This field is crucial for applications ranging from urban planning and traffic management to privacy preservation in mobility data and human movement analysis in healthcare, driving advancements in both theoretical understanding and practical deployment of trajectory-based systems.